An implantable cardiac device is a medical device that is implanted in a patient to monitor electrical activity of the heart and to deliver appropriate electrical and/or drug therapy, as required. Implantable cardiac devices include, for example, pacemakers, cardioverters and defibrillators. The term “implantable cardioverter defibrillator” or simply “ICD” is used herein to refer to any implantable cardiac device. An ICD employs a battery to power its internal circuitry and to generate electrical therapy. The electrical therapy can include, for example, pacing pulses, cardioverting pulses and/or defibrillator shock pulses.
Heart failure is a growing medical challenge. In clinical practice today, most patients are managed effectively through pharmacological therapy such as beta-blockers, ACE inhibitors, and diuretics. If a patient's condition worsens, treatment may become more aggressive to include biventricular pacing and other implantable cardiac device therapy. Along with providing the primary objectives in the treatment of heart failure of improving symptoms, increasing the quality of life, and slowing disease progression, devices need to provide heart failure physicians with diagnostic parameters to monitor the patient's progress.
Currently, medical history and physical examination are the most important tools that a physician uses to determine and mark the progress of a heart failure patient. This involves much of the physician's time with the patient, as this may lead to the primary management program for the patient.
Included in most management programs is an exercise routine. It has been written extensively that adherence to exercise is a priority in improving or in maintaining good heath. Exercise diagnostics may help clinicians assess the compliance of the management programs prescribed to their patients, and possibly assist the patient in meeting those goals.
During exercise, the heart rate is a parameter or indicator of the amount of work that was required to provide blood and oxygen to the body. The maximum heart rate for a level of exercise corresponds to the conditioning of the heart. Other parameters, such as heart rate intensity, percent oxygen consumption (% VO2) reserve, metabolic equivalents (METS), and workload also provide data that is indicative of heart conditioning.
Heart rate recovery after exercise is evaluated as a clinical marker of good vagal activity and cardiac health. As the heart rate increases due to a reduction in vagal tone, the heart rate also decreases with a reactivation of vagal activity. A delayed response to the decreasing heart rate may be a good prognostic marker of overall mortality (Cole, C. et al., NEJM 341:18, 1351-1357 (1999)) and cardiac health. Cole suggests that a reduction of only 12 beats per minute after one minute from peak exercise has been shown to be an abnormal value.
As previously mentioned, adherence to an exercise routine is a priority in managing heart failure progression; therefore, it is critical that a physician monitor significant patient activity, i.e., the time the patient is moving around in a potential exercise-like manner, and patient exercise, i.e., the time the patient is continuously moving around in an exercise-like manner. One method of monitoring patient activity and exercise relies on subjective and often inaccurate reporting of exercise duration and workload/intensity level by the patient.
Other more objective methods of monitoring patient activity and exercise rely on algorithms that monitor for significant patient activity by comparing patient activity data obtained through physiological sensors, against an activity threshold. Such algorithms may employ an automated process for initially setting the activity threshold using patient activity data collected over a period of time, after implant of the device. For some people, however, the initial activity threshold setting may overtime, result in system performance that is less than optimal. For example, an over-sensitive threshold value may cause the algorithm to consider a patient's daily activity such as office work, reading and talking as significant activity. Conversely, an under-sensitive threshold value may cause the algorithm to exclude low-level, significant activity, e.g., light walking, from its exercise diagnostic routine. Therefore, periodic verification, recalibration or optimization of the activity threshold is desirable to ensure accurate detection of, and distinction between, low-level, significant activity and non-significant activity.